AI RESEARCH
Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling
arXiv CS.AI
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ArXi:2605.30376v1 Announce Type: cross Modern time series architectures face a fundamental trade-off: channel-independent models scale well with increasing data volume but ignore critical inter-channel dependencies, while channel-dependent models are expressive but remain ``dimension-bounded'', struggling to generalize across heterogeneous datasets. To bridge this gap, we